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:: Volume 4, Issue 12 (a 2017) ::
2017, 4(12): 21-32 Back to browse issues page
Uplift capacity prediction of suction caisson in sand bend using GMDH and method GMDH-ANN
Mojtaba Masoumi , Mohamad javad Khanjani , Kourosh Qaderi
shahid bahonar university , mojtaba.masoumi@gmail.com
Abstract:   (2954 Views)

Suction caissons generally used as anchor for large offshore structures. Uplift capacity is the main issue in their stabilities. If this issue doesn’t calculate correctly, suction caisson may be collapsed. During recent years, many Artificial Intelligence (AI) has been used for suction caisson uplift capacity prediction.  One of this method is Group Method of Data Handling (GMDH). In this study, a model based on GMDH and a hybrid model GMDH-ANN were developed using programing code in MATLAB software. For validating developed methods, several statistical indices are calculated. Also the results of Finite Element Method (FEM) and Artificial Neural Network (ANN) were compared with developed methods. Comparison of these results showed that these developed methods had good performance in suction caisson uplift capacity.

Keywords: Suction caisson, GMDH, ANN, uplift capacity, power planet
Full-Text [PDF 761 kb]   (506 Downloads)    
Type of Study: Applicable | Subject: سد و سازه
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masoumi M, khanjani M J, qaderi K. Uplift capacity prediction of suction caisson in sand bend using GMDH and method GMDH-ANN. Iranian Dam and Hydroelectric Powerplant 2017; 4 (12) :21-32
URL: http://journal.hydropower.org.ir/article-1-111-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 4, Issue 12 (a 2017) Back to browse issues page
نشریه سد و نیروگاه برق آبی Journal of Dam and Hydroelectric Powerplant
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